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DBMS > Databricks vs. Elasticsearch vs. EsgynDB vs. Microsoft Azure Synapse Analytics vs. Sphinx

System Properties Comparison Databricks vs. Elasticsearch vs. EsgynDB vs. Microsoft Azure Synapse Analytics vs. Sphinx

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonElasticsearch  Xexclude from comparisonEsgynDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Relational DBMS
Search engineRelational DBMSRelational DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.databricks.comwww.elastic.co/­elasticsearchwww.esgyn.cnazure.microsoft.com/­services/­synapse-analyticssphinxsearch.com
Technical documentationdocs.databricks.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.microsoft.com/­azure/­synapse-analyticssphinxsearch.com/­docs
DeveloperDatabricksElasticEsgynMicrosoftSphinx Technologies Inc.
Initial release20132010201520162001
Current release8.6, January 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoElastic LicensecommercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, JavaC++C++
Server operating systemshostedAll OS with a Java VMLinuxhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesyes
Typing infopredefined data types such as float or dateyesyesyesno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnonono
Secondary indexesyesyes infoAll search fields are automatically indexedyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLSQL-like query languageyesyesSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary protocol
Supported programming languagesPython
R
Scala
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
Java
PHP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesJava Stored ProceduresTransact SQLno
Triggersyes infoby using the 'percolation' featurenonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesMulti-source replication between multi datacentersyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectoryesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noMemcached and Redis integrationno
User concepts infoAccess controlfine grained access rights according to SQL-standardyesno
More information provided by the system vendor
DatabricksElasticsearchEsgynDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksElasticsearchEsgynDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSphinx
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